Mobile health in preventive cardiology: current status and future perspective

Mobile Health Interventions: A Frontier for Mitigating the Global Burden of Cardiovascular Disease

Mobile health (mHealth) interventions have emerged as a promising approach for cardiovascular disease (CVD) prevention and management. The proliferation of smartphones and wearable devices enables convenient access to health monitoring tools, educational resources, and communication with healthcare providers. mHealth interventions encompass mobile apps, wearables, and telehealth services that empower users to monitor vital signs, adhere to medication, and adopt healthier lifestyles. Their effectiveness hinges on user engagement, leveraging behavioral science principles and gamification strategies. While mHealth offers advantages such as personalized support and increased reach, it faces challenges pertaining to data privacy, security concerns, and resistance from healthcare providers. Robust encryption and adherence to regulations like the Health Insurance Portability and Accountability Act (HIPAA) are crucial for safeguarding sensitive health data. Integrating mHealth into clinical workflows can enhance healthcare delivery, but organizational adjustments are necessary. The future of mHealth is closely intertwined with artificial intelligence (AI), enabling remote monitoring, predictive algorithms, and data-driven insights. Tech giants are incorporating advanced health-tracking capabilities into their devices, paving the way for personalized wellness approaches. However, mHealth grapples with ethical dilemmas surrounding data ownership, privacy breaches, and inadvertent data capture. Despite its potential, mHealth necessitates a concerted effort to overcome obstacles and ensure ethical, secure, and practical implementation. Addressing technical challenges, fostering standardization, and promoting equitable access are pivotal for unlocking the transformative impact of mHealth on cardiovascular health and reducing the global burden of CVD.

Advancing telemedicine in cardiology: A comprehensive review of evolving practices and outcomes in a postpandemic context

Telemedicine, telehealth, e-Health, and other related terms refer to the exchange of medical information or medical care from one site to another through electronic communication between a patient and a health care provider. As telemedicine infrastructure has changed since the coronavirus disease 2019 (COVID-19) pandemic, this review provides an overview of telemedicine use and effectiveness in cardiology, with emphasis on coronary artery disease in the postpandemic context. Prepandemic studies tend to report statistically insignificant or modest improvements in cardiovascular disease outcome from telemedicine use to usual care. In contrast, postpandemic studies tend to report positive outcomes or comparable acceptance of telemedicine use to usual care. Today, telemedicine can effectively replace in person follow-up visits to produce comparable (but not necessarily superior) outcomes in cardiovascular disease management. A benefit of telemedicine is the potential reduction in follow-up time or time to intervention, which may lead to earlier detection and prevention of adverse events. Nonetheless, barriers remain to effective telemedicine implementation in the postpandemic context. Ensuring accessible and user-friendly telemedicine devices, maintaining adherence to remote rehabilitation procedures, and normalizing use of telemedicine in routine follow-up visits are examples. Current knowledge gaps include the true economic cost of telemedicine infrastructure, feasibility of use in specific cardiology contexts, and sex/gender differences in telemedicine use. Future telemedicine developments will need to address these concerns before acceptance of telemedicine as the new standard of care.

Mapping Factors That Affect the Uptake of Digital Therapeutics Within Health Systems: Scoping Review

BACKGROUND

Digital therapeutics are patient-facing digital health interventions that can significantly alter the health care landscape. Despite digital therapeutics being used to successfully treat a range of conditions, their uptake in health systems remains limited. Understanding the full spectrum of uptake factors is essential to identify ways in which policy makers and providers can facilitate the adoption of effective digital therapeutics within a health system, as well as the steps developers can take to assist in the deployment of products.

OBJECTIVE

In this review, we aimed to map the most frequently discussed factors that determine the integration of digital therapeutics into health systems and practical use of digital therapeutics by patients and professionals.

METHODS

A scoping review was conducted in MEDLINE, Web of Science, Cochrane Database of Systematic Reviews, and Google Scholar. Relevant data were extracted and synthesized using a thematic analysis.

RESULTS

We identified 35,541 academic and 221 gray literature reports, with 244 (0.69%) included in the review, covering 35 countries. Overall, 85 factors that can impact the uptake of digital therapeutics were extracted and pooled into 5 categories: policy and system, patient characteristics, properties of digital therapeutics, characteristics of health professionals, and outcomes. The need for a regulatory framework for digital therapeutics was the most stated factor at the policy level. Demographic characteristics formed the most iterated patient-related factor, whereas digital literacy was considered the most important factor for health professionals. Among the properties of digital therapeutics, their interoperability across the broader health system was most emphasized. Finally, the ability to expand access to health care was the most frequently stated outcome measure.

CONCLUSIONS

The map of factors developed in this review offers a multistakeholder approach to recognizing the uptake factors of digital therapeutics in the health care pathway and provides an analytical tool for policy makers to assess their health system's readiness for digital therapeutics.

Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review

BACKGROUND

Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society.

OBJECTIVE

This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations.

METHODS

The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature.

RESULTS

In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations.

CONCLUSIONS

The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.

Racial and Ethnic Disparities in All-Cause and Cardiovascular Mortality Among Cancer Patients in the U.S

Background

With improved cancer survival, death from noncancer etiologies, especially cardiovascular disease (CVD) mortality, has come more into focus. Little is known about the racial and ethnic disparities in all-cause and CVD mortality among U.S. cancer patients.

Objectives

This study sought to investigate racial and ethnic disparities in all-cause and CVD mortality among adults with cancer in the United States.

Methods

Using the Surveillance, Epidemiology, and End Results (SEER) database from years 2000 to 2018, all-cause and CVD mortality among patients ≥18 years of age at the time of initial malignancy diagnosis were compared by race and ethnicity groups. The 10 most prevalent cancers were included. Cox regression models were used to estimate adjusted HRs for all-cause and CVD mortality using Fine and Gray's method for competing risks, as applicable.

Results

Among a total of 3,674,511 participants included in our study, 1,644,067 (44.7%) died, with 231,386 (6.3%) deaths as a result of CVD. After adjusting for sociodemographic and clinical characteristics, non-Hispanic (NH) Black individuals had both higher all-cause (HR: 1.13; 95% CI: 1.13-1.14) and CVD (HR: 1.25; 95% CI: 1.24-1.27) mortality, whereas Hispanic and NH Asian/Pacific Islander had lower mortality than NH White patients. Racial and ethnic disparities were more prominent among patients 18 to 54 years of age and those with localized cancer.

Conclusions

Significant racial and ethnic differences exist in both all-cause and CVD mortality among U.S. cancer patients. Our findings underscore the vital roles of accessible cardiovascular interventions and strategies to identify high-risk cancer populations who may benefit most from early and long-term survivorship care.

Associations of Demographic, Socioeconomic, and Cognitive Characteristics With Mobile Health Access: MESA (Multi-Ethnic Study of Atherosclerosis)

Background

Mobile health (mHealth) has an emerging role in the prevention of cardiovascular disease. This study evaluated possible inequities in mHealth access in older adults.

Methods and Results

mHealth access was assessed from 2019 to 2020 in MESA (Multi‐Ethnic Study of Atherosclerosis) telephone surveys of 2796 participants aged 62 to 102 years. A multivariable logistic regression model adjusted for general health status assessed associations of mHealth access measures with relevant demographic, socioeconomic, and cognitive characteristics. There were lower odds of all access measures with older age (odds ratios [ORs], 0.37–0.59 per 10 years) and annual income <$50 000 (versus ≥$50 000 ORs, 0.55–0.62), and higher odds with higher Cognitive Abilities Screening Instrument Score (ORs, 1.22–1.29 per 5 points). Men (versus women) had higher odds of internet access (OR, 1.32 [95% CI,1.05–1.66]) and computing device ownership (OR, 1.31 [95% CI, 1.05–1.63]) but lower fitness tracker ownership odds (OR, 0.70 [95% CI, 0.49–0.89]). For internet access and computing device ownership, we saw lower odds for Hispanic participants (versus White participants OR, 0.61 [95% CI, 0.44–0.85]; OR, 0.69 [95% CI, 0.50–0.95]) and less than a high school education (versus bachelor's degree or higher OR, 0.27 [95% CI, 0.18–0.40]; OR, 0.32 [95% CI, 0.28–0.62]). For internet access, lower odds were seen for Black participants (versus White participants OR, 0.64 [95% CI, 0.47–0.86]) and other health insurance (versus health maintenance organization/private OR, 0.59 [95% CI, 0.47–0.74]). Chinese participants (versus White participants) had lower internet access odds (OR, 0.63 [95% CI, 0.44–0.91]) but higher computing device ownership odds (OR, 1.87 [95% CI, 1.28–2.77]).

Conclusions

Among older‐age adults, mHealth access varied by major demographic, socioeconomic, and cognitive characteristics, suggesting a digital divide. Novel mHealth interventions should consider individual access barriers.

Registration

URL: https://www.clinicaltrials.gov/; Unique identifier: NCT00005487.

Life's Essential 8: Updating and Enhancing the American Heart Association's Construct of Cardiovascular Health: A Presidential Advisory From the American Heart Association

In 2010, the American Heart Association defined a novel construct of cardiovascular health to promote a paradigm shift from a focus solely on disease treatment to one inclusive of positive health promotion and preservation across the life course in populations and individuals. Extensive subsequent evidence has provided insights into strengths and limitations of the original approach to defining and quantifying cardiovascular health. In response, the American Heart Association convened a writing group to recommend enhancements and updates. The definition and quantification of each of the original metrics (Life's Simple 7) were evaluated for responsiveness to interindividual variation and intraindividual change. New metrics were considered, and the age spectrum was expanded to include the entire life course. The foundational contexts of social determinants of health and psychological health were addressed as crucial factors in optimizing and preserving cardiovascular health. This presidential advisory introduces an enhanced approach to assessing cardiovascular health: Life's Essential 8. The components of Life's Essential 8 include diet (updated), physical activity, nicotine exposure (updated), sleep health (new), body mass index, blood lipids (updated), blood glucose (updated), and blood pressure. Each metric has a new scoring algorithm ranging from 0 to 100 points, allowing generation of a new composite cardiovascular health score (the unweighted average of all components) that also varies from 0 to 100 points. Methods for implementing cardiovascular health assessment and longitudinal monitoring are discussed, as are potential data sources and tools to promote widespread adoption in policy, public health, clinical, institutional, and community settings.

Efficacy of supermarket and web-based interventions for improving dietary quality: a randomized, controlled trial

Dietary interventions may best be delivered at supermarkets, which offer convenience, accessibility, full food inventories and, increasingly, in-store registered dietitians, online shopping and delivery services. In collaboration with a large retail supermarket chain, we conducted a multisite supermarket and web-based intervention targeting nutrition trial (no. NCT03895580), randomizing participants (n = 247 (139 women and 108 men)) 2:2:1 to two levels of dietary education (Strategy 1 and Strategy 2) or an enhanced control group that included educational components beyond the routine standard of care. Both Strategies 1 and 2 included individualized, in-person, dietitian-led, purchasing data-guided interventions. Strategy 2 also included online tools for shopping, home delivery, selection of healthier purchases, meal planning and healthy recipes. The primary endpoint was change in dietary approaches to stop hypertension (DASH) score (a measure of adherence to the DASH diet) from baseline to 3 months. The primary endpoint was met because, at 3 months, the DASH score increased by 4.7 more for the combined Strategy 1 and Strategy 2 groups than for the control group (95% confidence interval (CI) (0.9, 8.5), P = 0.02). In a prespecified hierarchical test, at 3 months, DASH score increased by 3.8 more for the Strategy 2 group than for the Strategy 1 group (95% CI (0.8, 6.)9, P = 0.01). This trial demonstrates the efficacy of data-guided, supermarket-based, dietary interventions and modern online shopping tools in improving dietary quality in a free-living, community-based population. The trial also demonstrates the opportunity for academic investigators to collaborate with retailers to design and rigorously test comprehensive healthcare interventions.

Smartphone applications managing antithrombotic therapy: a scoping literature review (Preprint)

Background

Antithrombotic therapy is complex and requires informed decisions and high therapy adherence. Several mobile phone apps exist to either support physicians in the management of antithrombotic therapies or to educate and support patients. For the majority of these apps, both their medical evidence and their development background are unknown.

Objective

This review aims to investigate the available literature describing high-quality apps for managing antithrombotic therapy based on professional scientific information.

Methods

Keywords and Medical Subject Heading terms were used to search MEDLINE via PubMed and Ovid between December 2019 and January 2022. Inclusion criteria were the availability of full text and publications in the English language. Apps that solely focused on atrial fibrillation were excluded. Qualitative findings were thematically synthesized and reported narratively.

Results

Out of 149 identified records, 32 were classified as eligible. We identified four groups: (1) apps for patients supporting self-management of vitamin K antagonists, (2) apps for patients increasing therapy adherence, (3) educational apps for patients, and (4) apps for physicians in supporting guideline adherence.

Conclusions

Throughout the evaluated data, patients from all age groups receiving antithrombotic drugs expressed the desire for a digital tool that could support their therapy management. In addition, physicians using mobile guideline-based apps may have contributed to decreased adverse event rates among their patients. In general, digital apps encompassing both user-friendly designs and scientific backgrounds may enhance the safety of antithrombotic therapies. However, our evaluation did not identify any apps that addressed all antithrombotic drugs in combination with perioperative stratification strategies. Currently, strict regulations for smartphone apps seem to negatively affect the development of new apps. Therefore, new legal policies for medical digital apps are urgently needed.